A Stochastic Optimization Model for Commodity Rebalancing Under Traffic Congestion in Disaster Response

Abstract

Part 1: Smart Supply Networks; International audience; After a large-scale disaster, the emergency commodity should be distributed to relief centers. However, the initial commodity distribution may be unbalanced due to the incomplete information and uncertain environment. It is necessary to rebalance the emergency commodity among relief centers. Traffic congestion is an important factor to delay delivery of the commodity. Neither the commodity rebalancing nor traffic congestion is considered in previous studies. In this study, a two-stage stochastic optimization model is proposed to manage the commodity rebalancing, where uncertainties of demand and supply are considered. The goals are to minimize the expected total weighted unmet demand in the first stage and minimize the total transportation time in the second stage. Finally, a numerical analysis is conducted for a randomly generated instance; the results illustrate the effectiveness of the proposed model in the commodity rebalancing over the transportation network with traffic congestion.

Document type: Conference object

Original document

The different versions of the original document can be found in:

• http://link.springer.com/content/pdf/10.1007/978-3-030-29996-5_11,

http://dx.doi.org/10.1007/978-3-030-29996-5_11 under the license http://creativecommons.org/licenses/by/

• https://dblp.uni-trier.de/db/conf/ifip5-7/apms2019-2.html#Gao19,

https://link.springer.com/chapter/10.1007%2F978-3-030-29996-5_11,

https://rd.springer.com/chapter/10.1007/978-3-030-29996-5_11,

https://academic.microsoft.com/#/detail/2969849309 under the license http://www.springer.com/tdm

• https://hal.inria.fr/hal-02460520,

https://hal.inria.fr/hal-02460520/document,

https://hal.inria.fr/hal-02460520/file/489108_1_En_11_Chapter.pdf

under the license http://creativecommons.org/licenses/by/